class_docstr: HarmonicPercussiveSourceSeparation is a Processor which separates the
  magnitude spectrogram into its harmonic and percussive components with
  median filters.
  
  Parameters
  ----------
  masking : float or str
      Can be either the literal 'binary' or any float coefficient resulting
      in a soft mask. 'None' translates to a binary mask, too.
  harmonic_filter : tuple of ints
      Tuple with harmonic filter size (frames, bins).
  percussive_filter : tuple of ints
      Tuple with percussive filter size (frames, bins).
  
  References
  ----------
  .. [1] Derry FitzGerald,
         "Harmonic/percussive separation using median filtering.",
         Proceedings of the 13th International Conference on Digital Audio
         Effects (DAFx), Graz, Austria, 2010.
docstr: Returns the harmonic and percussive slices of the data.
  
  Parameters
  ----------
  data : numpy array
      Data to be sliced (usually a magnitude spectrogram).
  
  Returns
  -------
  harmonic_slice : numpy array
      Harmonic slice.
  percussive_slice : numpy array
      Percussive slice.
docstr_tok: ["Returns","the","harmonic","and","percussive","slices","of","the","data",".","Parameters","--","--","--","--","--","data",":","numpy","array","Data","to","be","sliced","(","usually","a","magnitude","spectrogram",")",".","Returns","--","--","--","-","harmonic_slice",":","numpy","array","Harmonic","slice",".","percussive_slice",":","numpy","array","Percussive","slice","."]
code: def slices(self, data):
      """
      Returns the harmonic and percussive slices of the data.
  
      Parameters
      ----------
      data : numpy array
          Data to be sliced (usually a magnitude spectrogram).
  
      Returns
      -------
      harmonic_slice : numpy array
          Harmonic slice.
      percussive_slice : numpy array
          Percussive slice.
  
      """
      from scipy.ndimage.filters import median_filter
  
      # compute the harmonic and percussive slices
      harmonic_slice = median_filter(data, self.harmonic_filter)
      percussive_slice = median_filter(data, self.percussive_filter)
      # return the slices
      return harmonic_slice, percussive_slice
  
file_path: madmom/madmom/audio/hpss.py
imports: from __future__ import absolute_import, division, print_function
  import numpy
  from madmom.processors import Processor
label_desc: Use image node_id 2 for calling the HarmonicPercussiveSourceSeparation obj's underlying member method code with example usage: obj.slices(data) and returns: harmonic_slice,  percussive_slice